R Programming: From the Classroom to the Real World
By Jay Emerson, Yale University
Date: Monday, May 2, 2016
Registration begins at 8:30 am, course begins at 9:00 am
Continental breakfast and lunch are provided
Dear Fellow Statisticians and ASA Members:
Jay Emerson from Yale University will present a one-day short course titled, "R Programming: From Classroom to the Real World" on Monday, May 2, 2016 on the campus of Penn State Great Valley, Malvern, PA.
John W. Emerson (Jay) is Director of Graduate Studies and Associate Professor, Adjunct, in the Department of Statistics at Yale University. His work with the S language extends back to 1990 and he was one of the earliest adopters of R for introductory statistics courses (circa 2002). His mosaicplot() function is included in the base distribution of R and he is the author of a range of packages for data exploration and visualization (ggpairs, YaleToolkit, . . . ), Bayesian change point analysis (bcp), and “Big Data” analysis (bigmemory and others). He frequently teaches workshops to clients in government and industry, and has taught summer courses and workshops at universities around the world.
Detailed information on the short course can be found below. Registration for the event can be done at: eventbrite.com
I hope you can attend.
Robin Mogg Secretary, ASA Philadelphia Chapter
This course both provides a “hands on” introduction to, and review of, the core R language and teaches essentials of R programming to R users at a range of levels. It uses real-world data problems accessible to all audiences. Specifically, there are two target audiences:
- instructors at all levels who aspire to use R in their courses and for their research
- practitioners who seek to add R to their portfolio and become more productive in outside-the-box problem solving
These audiences are more similar than you might expect and can learn from each other in workshop exercises solving real-world data challenges. The distinction between programming (or scripting) with R and using R is an important one. Most people can use R as a tool for a small number of focused tasks that fit neatly into different boxes. This workshop emphasizes problem solving outside-the-box where no single function or package is likely to be sufficient. The process is as important as the solution, and this approach to the R language is invaluable in the classroom and in the real world.
- The core language syntax and data structures for working with and exploring data. Accessing and organizing data; arithmetic and logical operators; conditional arguments; loops; subsetting; common functions; getting help and using extension packages.
- Graphics: focusing on base graphics but with a quick introduction to ggplot2. Graphical output formats from traditional explorations to (depending on the workshop level and focus) the interactive via shiny apps.
- Data cleaning/munging/scraping/manipulation/tidying. Let’s face it: getting ready for the analysis often seems like 95% of the work. In fact, our work is usually a seemingly endless iterative process of exploring, manipulating, visualizing, cleaning/manipulating, and so on. While no workshop can give you everything you will need, this workshop will build a solid foundation for your future work.
- An introduction to parallel computing and some more advanced topics related to high-performance computing.